Articles tagged with Biological Models
Researchers developed an algorithm using amino acid sequences of proteins called T cell receptors to predict patient response to treatment, providing insights into the biology behind an effective response. The algorithm, DeepTCR, identified patterns that are predictive of patient response as accurately as known biomarkers.
Researchers at Michigan Medicine found a strong association between lower grip strength and accelerated biological aging in middle-aged and older adults. This study provides evidence that maintaining muscle strength across the lifespan may help protect against age-related diseases.
The study reveals that a genetic mutation can accelerate the body's internal clock, leading to improved adjustment to shift work schedules. The findings have implications for understanding the health consequences of circadian misalignment and developing medical treatments.
A new study published in GigaScience has made available an enormous amount of behavioral data from an animal model of obsessive-compulsive disorder (OCD), comprising over 2 years of continuous recording. The data set, which is the culmination of a 15-year study, provides insights into the mechanisms of OCD and potential treatments.
A new genome imaging technique captures the structure of the human genome at unprecedented resolution, revealing how individual genes fold and work. This technique, called Modeling immuno-OligoSTORM (MiOS), combines high-resolution microscopy and advanced computational modeling to provide a detailed picture of gene shape and function.
Mathematicians at Aston University are developing computational modelling techniques to examine biological drag reduction methods, such as fish slime secreted by predator-avoiding fish. This project aims to reduce skin-friction drag and increase the performance range of electric vehicles, contributing to a reduction in CO2 emissions.
A new study by OIST researchers has developed a model that determines variations in the speed of DNA copying proteins in bacterial genomes. The model shows that certain sections of DNA are copied faster than others, and this variation is linked to an increased error rate, which could have implications for mutation rates.
Researchers developed a machine learning algorithm that can generate a continuous 3D model of cells from a partial set of 2D images. The neural field network learns a mapping from spatial coordinates to physical quantities, allowing for smooth zooming and no pixelation.
A University of Missouri researcher and his team are using artificial intelligence to study anatomical research, creating detailed 3D computer models of muscles. This technology is advancing the field by enabling researchers to analyze muscle fiber orientation and develop a better understanding of motor control in animals.
A new study from MIT reveals that computer models predicting molecular interactions, like AlphaFold, need improvement to help identify drug mechanisms of action. Researchers improved the performance of these models using machine-learning techniques, but more work is needed.
A new study from North Carolina State University shows that soil temperature can be used to predict the spread of the corn earworm, an important pest affecting various crop species. The research reveals three geographic zones where the pest can overwinter, and models suggest that these zones will shift northward due to climate change.
Scientists modeled how different coronavirus shapes affect rotational diffusivity, impacting transmission and infective success. The study found that more elongated shapes result in slower rotation rates, potentially improving attachment to cells.
Researchers develop a new coarse-graining approach that enables the prediction of patterns on small scales, reducing complexity by focusing on total densities of particles. The model is applied to the Min protein system, which controls cell division in bacteria, and experimental results confirm theoretical predictions.
A research team used game theory to analyze cooperation in networks and found that networks with a high level of cooperation can emerge if individuals take a clear-cut position against free riders. The study also showed that if contributors leave an environment too quickly, it leads to a lower level of cooperation.
Undergraduate students at Ohio University applied kinetic techniques learned in physical chemistry to analyze the COVID-19 spread data from the CDC. They developed a model that considers the effect of vaccination and made predictions for the following months, correctly predicting the surge in cases in Ohio.
A new mathematical framework predicts the most effective combinations of drugs to treat postmenopausal bone loss in patients. The model identifies optimal orderings that boost bone density and reduce long-term bone loss, improving treatment outcomes.
Two OU research groups received nearly $2 million in funding to develop new surveillance methods and predict the next avian influenza pandemic. The projects focus on integrating data from multiple sources to detect early signals of disease spread.
Researchers developed a mathematical model to predict the efficiency of nanoparticle delivery into cells, particularly in stem cells. They found that nanoparticles become trapped in bubble-like vesicles, preventing them from reaching their targets.
Researchers at the University of Illinois Urbana-Champaign have developed a low-cost ultrasound imaging method to study the relationship between Alzheimer's disease and the brain's vascular system. The technique, which provides high-resolution images of animal microvasculature, may aid in early detection of the disease.
Hawks use a unique flight path to slow down to a safe speed while minimizing the distance from the perch at which they stall. This allows them to control their landings effectively, even when slowing down risks stall, leading to sudden loss of flight control.
A recent study out of the Complexity Science Hub Vienna developed a mathematical and computational framework for analysing neural activity in C. elegans, a tiny worm used to study neural activity. The study proposes a way to unmask the roles of neurons by using more natural perturbations.
Researchers at University of Missouri, Georgia Tech and Harvard University have successfully demonstrated a new Type 1 diabetes treatment in large animal models. By transplanting pancreatic islet cells with a molecule called FasL, they prevent rogue immune cells from destroying the transplanted cells.
A team of researchers used a CRISPR-based approach to study the evolution of lung cancer cells, tracking their history from the first activation of cancer-causing mutations. The study revealed significant diversity between subpopulations of cells within the same tumor, with certain groups becoming more fit and aggressive over time.
Researchers at DTU Compute and DIKU have developed a machine learning model that can map the potential of proteins, enabling the biotech industry to accelerate the development of new proteins. The model generates a picture of how proteins are linked, allowing for the identification of closely related proteins with desirable properties.
Researchers used Frontera supercomputer to model coronavirus-receptor interactions, discovering a 'one-two punch' combo that primes virus for fusion. The study provides new understanding of the mechanism behind increased virulence of variants such as delta and omicron.
Scientists have developed Community Distribution Models (CDMs) to predict upland vegetation communities from published data at a national scale. The approach uses publicly available and open-access NVC records and environmental data, with models based on random forests being the most accurate.
A team of researchers developed a novel chip-based infection model to study invasive aspergillosis, a mold infection that affects the lungs. The model allows for live microscopic observation of damage caused by fungal hyphae and the response of immune cells.
Researchers at Stevens Institute of Technology are pushing through technical barriers in organ printing by leveraging decades-old technique and computational modeling. The team aims to create any type of organ at any time, including skin on an open wound, using microfluidic bio-printing.
A new study used a virtual population to simulate a clinical trial examining kidney damage in Black Americans. The model predicted kidney damage and showed that adding drug therapy and reducing salt intake could stop the damage, improving heart sizes as well.
Researchers at the University of Maine used zebrafish to test the effectiveness of neuromuscular electrical stimulation (NMES) on muscle strength and structure. The study found that only one NMES regimen, endurance neuromuscular stimulation (eNMES), improved muscle health when combined with an antioxidant and a specific receptor.
Autophagy is induced when ER-bound ribosomes are stalled, rescuing them from cellular harm. The ERC grant aims to decipher the role of Autophagy in rescuing stalled ER-bound ribosomes.
A recent study found that large US firms have lower product diversity, with companies manufacturing similar products becoming more common. This decrease in product diversity could be due to various factors such as narrowing consumer demand and data biases in the analysis.
Researchers from the University of Illinois have revamped the popular crop growth simulation software BioCro, allowing modelers to use the technology more easily. The updated version includes faster and more accurate algorithms, enabling researchers to try new simulations more easily and link to other models.
Researchers studied microorganisms, including TB bacteria, to understand how genetic mutations drive adaptation and resistance. They found that certain types of mutations are more common than others, and this imbalance can help scientists predict which mutations will lead to drug resistance.
Researchers have developed a machine learning framework called dynamo that can predict a cell's path over time, including its fate and genetic changes. The tool uses data from individual cells to create mathematical equations describing the cell's trajectory.
Researchers created a computer model that simulates the way slime moulds construct their network, finding networks with improved travel time or resilience to disruption. The models were validated using three key metrics and showed good correlation with actual slime mould results.
Scientists at the University of Missouri discovered that bisphenol A (BPA) exposure during pregnancy can negatively impact fetal brain development. MicroRNAs in the placenta play a key role in regulating cellular functions, including neural development. Researchers believe that microRNA packages could reach the brain through the placen...
The European Research Council has awarded Kai Kretzschmar a Starting Grant to systematically characterise oral epithelial stem cells. This will help decipher the mechanisms underlying the diversity of the oral epithelium and its contribution to oral squamous cell carcinomas.
A new study published in PLOS Computational Biology found that the order of COVID-19 symptoms varies depending on the SARS-CoV-2 variant. In the USA, cough was most likely to be the first symptom, while fever and diarrhea were more common third symptoms.
Researchers found that theropods strengthened their jaws through time, with expanding rear jaw portions and evolving different jaw shapes depending on diet. This allowed them to exploit a wider range of food items and minimized bone fracture risk.
Researchers at the University of Ottawa have made a breakthrough in reversing memory deficits and slowing disease progression in female mouse models of Alzheimer's disease. The study found that activating a specific receptor was effective in treating females, who make up two-thirds of diagnosed cases.
Researchers created novel frog models to replicate polycystic kidney disease, allowing for real-time observation of disease processes. AI analysis enabled rapid assessment of disease in the tiny animals.
Damaged coral reefs exhibit a two-phase recovery pattern, with the first phase lasting up to six years, and the second phase being faster. This pattern was observed in 60% of severely disturbed reefs on the Great Barrier Reef.
A new algorithm has been developed to train spiking neural networks, mimicking the human brain's structure and function. This approach enables these powerful, fast, and energy-efficient systems to solve complex tasks like image classification with high precision.
Researchers have found four commonly used medications that can reverse Alzheimer's disease in mice by addressing the underlying causes of the condition. The study identifies non-steroidal anti-inflammatories and anti-hypertensives as effective treatments, paving the way for early diagnosis and potential therapy.
Researchers developed a mathematical model to predict the spread of COVID-19, taking into account restrictions and containment policies. The model successfully calculated the total number of infected and peak infection days in the 2014-2015 Ebola virus epidemic.
Researchers used machine learning on UK Biobank data to create proxy measures for brain age, intelligence, and neuroticism traits. These indirect measurements strongly correlate with specific diseases or outcomes, offering a potential solution for mental health diagnoses.
The BiCIKL project links biodiversity data types and classes across 14 European institutions, creating a Biodiversity Knowledge Hub for seamless access. This initiative streamlines Open Science and FAIR practices, empowering researchers with efficient tools to explore and utilize biodiversity data.
A new study found that local mobility, primary care access, and limited contacts in contagion hubs can curb COVID-19 deaths. The researchers used novel statistical approaches to analyze mortality curves across 20 Italian regions, identifying a strong association between mobility and COVID mortality.
A new study from Washington University in St. Louis shows that guided by sparsity, silicon neurons learn to pick the most energy-efficient perturbations and wave patterns, enabling an emergent phenomenon of efficient communication between neurons. This research has significant implications for designing neuromorphic AI systems.
Researchers found that mice can make fine visual discriminations between slightly different lines, suggesting a more complex decision-making process than previously thought. The study's findings highlight the importance of considering non-perceptual biases in understanding animal behavior and decision-making strategies.
Researchers propose using patient-specific digital twins to model viral infections, integrating human physiology, immunology, and real-time clinical data. Medical digital twins could aid in optimizing treatments for individual COVID-19 patients, combining mechanistic knowledge with observational data and artificial intelligence.
New research from Cold Spring Harbor Laboratory highlights the importance of model evaluation in neuroscience. By building and comparing several models of neural signaling, researchers found that good predictive power does not necessarily indicate a model's representation of real neural networks.
A new study predicts a 36% global increase in invasive insect species by 2050, with Europe and Asia experiencing the strongest invasions. This research provides a baseline for assessing future biological invasions, enabling proactive measures to contain their spread.
A new model of breast cancer's causes, called Paradigm II, illustrates the dynamic and sometimes unexpected interactions between biological, behavioral, social, and physical domains. The model, created by a multidisciplinary team, includes 96 potential interactions and is available online for further research and discussion.
Nowzari's research uses network systems expertise to model how people's movement affects virus spread, providing a more nuanced approach than existing lumped population models. His goal is to help inform policy and business decisions by highlighting the impact of networking effects.
Researchers developed two experimental devices to study the harmful effects of hyperperistalsis on synthetic uterine tissue. The study found that peristaltic shear stresses caused alterations to endometrial epithelial cells and myometrial smooth muscle cells.
Neuroscientists at York University developed five predictive models using non-motor clinical and biological variables to detect early-stage Parkinson's disease. The models achieved over 80% accuracy in distinguishing early-stage Parkinson's from healthy controls, offering a potential alternative to traditional diagnosis methods.
A new study suggests that life in the universe is likely to be common, but only under specific conditions. The research, led by Professor Tomonori Totani, found that complex RNA structures necessary for life to exist may have formed spontaneously in vast regions of space beyond our observable horizon.
Joyce Tait discusses re-engineering biological components through computational modelling and bio-systems design technologies. She emphasizes the need for an equitable balance between promoting innovation and ensuring safety in synthetic biology.